Today we visited DANS (Data Archiving and Network Services). The first lecture we listened to was from Andrea Scharnhorst and she gave us more clarity around the role of DANS and the dilemmas of a research data archive. Some of the concepts were a little bit over my head because I don’t have much of a background in data archiving systems and the implications of digital data storage and dissemination, but I was really interested in thinking about two specific concepts she talked about; the implications of curating digital data and the divide between the “visible” and “invisible” factors informing research practices and results.
Data interpretation and collection is a direct product of the researcher’s positionality and what they deem relevant/important or not. It’s always important to be critical of data sets and question the intention of the researcher and data collectors in order to make the most of the data for your own use.
Andrea Scharnhorst made it clear that there is a divide between the visible gears of research and the more invisible/external factors that impact research. The visible and obvious research categories that influence each other are the input, output, and the actual research. The external ones are access educational resources and support systems such as access to housing and computer centers. Without analyzing the impact the external and seemingly disconnected factors have on the central factors the data is only able to be partially analyzed. As Andrea mentioned, data reflects the positionally of the researcher. If their positionally is not analyzed and understood it is harder to contextualize and understand what their research is really trying to say. As Kathleen Gregory said in her presentation, “Data doesn’t stand alone” and this also implied the positionally of the researcher.
Kathleen Gregory’s presentation really resonated with me. As an intended digital geography major I am intrigued by the idea of fair data and what makes data and digital information and patterns accessible and useful for all. She made it clear that search and data is not simply a set of technical procedures or results, but a highly subjective and mediated process. Data results that are returned are informed first by what we already know or don’t know. Digital patterns of connection and searching and sorting shape who knows who, who sees what, and who sees different content. Some questions she brought up were…
Who should be able to find data?
What should be able to be found?
Where should data be found?
What is available for who and when?
Why do people have access to data or not?
These questions represent the importance of understanding the intersection of technology, research, empathy, and social awareness when analyzing data accessibility. Different people require access to different types of data (observational, experimental…), but it’s difficult and unrealistic to assume that only one type of person or source will use the data or need access to it. This is when empathy and human-centered design thinking becomes imperative for successful data sharing.
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